Abstract Computerized adaptive testing (CAT) targets to accurately assess the student’s proficiency in the required subject/area. The key issue is how to design a question selector that adaptively selects the best-suited questions for each student based on previous performance step by step. Most existing question selectors execute via greedy metric functions (e. https://fitnessgravesyardes.shop/product-category/short-handrail/
A novel computerized adaptive testing framework with decoupled learning selector
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